Static stability within and just above the boundary layer was evaluated based on radiosonde profiles of virtual potential temperature. An artificial neural network data analysis approach known as self-organizing maps (SOMs) was used to objectively identify the range of virtual potential temperature profiles. The virtual potential temperature profiles, up to 1 km, are from ~1400 MOSAiC radiosonde observations and vertical profiles from the multi-model ensemble corresponding to the location of MOSAiC. Initial results indicate that CAFS reproduced the full range of observed stability profiles, but not necessarily with the correct frequency or at the correct time. Based on the SOM analysis, boundary layer stability regimes were defined by near surface stability and stability just above the boundary layer for both the radiosonde and model profiles. The results show that CAFS underrepresents the frequency of strong stability, particularly when the strong stability occurs just above the boundary layer. Radiation and wind observations were used to assess impacts of varying surface energy budget and wind shear on boundary layer stability and determine if these boundary layer forcings were accurately depicted in the models. Downwelling longwave radiation and 10 m wind speed corresponding to each stability regime were found to have too great a magnitude in CAFS compared to the observations, with the largest differences for the strongest stability regimes.

